1. Field of the Invention
The invention relates to a method for computation of the state variables of a hybrid differential-algebraic process model (hybrid DAP=hDAP) in succeeding time steps on a process computer with a process interface, the process computer being set up such that, via the process interface, at least one process variable of a physical process can be detected by the process computer and/or an output for influencing the physical process can be output, and in a computation process a current mode of the hybrid DAP is determined by evaluating the state variables, for deviation of the current mode of the hybrid DAP from the mode of the hybrid DAP which applies beforehand an executable mode-specific process model which corresponds to the current mode is chosen from the group of executable mode-specific process models and the further computation is based on it. The invention furthermore relates to a process computer with a process interface for coupling of the process computer to a physical process, with the process computer at least one process variable of a physical process being detectable via the process interface and/or one output being able to be output for influencing the physical process.
2. Description of Related Art
Process computers and methods of the above described type which are to be executed on process computers are quite generally used in technical problem formulations to specifically observe a physical process and/or to specifically influence this physical process in order to influence it in the desired manner. Often, process models—therefore functional physical-technical relationships which can be described by mathematical equations—are implemented on these process computers and for example, for control purposes constitute a mathematical model of the linked physical process, or mathematically simulate a process which is different from the linked physical process and which simulates a part of reality for example, for excitation of the “real” physical process, as is known for example, of simulators. These process computers, especially from the domain of control device development (rapid control prototyping, hardware-in-the-loop tests), can no longer be dispensed with.
Depending on the type of process which is to be computed and modeled on the process computer, the process model has different mathematical properties. Many process models consist of a system of linear or nonlinear differential equations, in the simplest case of a single differential equation. These differential equations are solved with the known numerical methods. Since the process computer is conventionally joined to a real physical process, it is necessary to compute the process model in real time so that process variables of the physical process can be detected and further processed in the desired time reference—defined by the succeeding time steps on the process computer—, and outputs for influencing the physical process can be output from the process computer.
Many process models, in addition to differential equations or systems of differential equations, also comprise algebraic equations which typically describe the behavior of conservation variables in the process. Simple relationships of this type are for example, currents in nodes of an electrical network, the energy constancy in a closed system, the volumetric flow of an incompressible medium, the conservation of momentum in a multibody system and other secondary kinetic conditions. These models are called differential-algebraic process models, hereinafter abbreviated “DAP”.
DAP are often structurally-invariant, i.e., they fix the state variables of the process model and the relationships between the state variables a priori, the mathematical framework as such does not change, neither over time nor depending on other conditions. These systems can be transferred into a complete algorithmic model—for example, in the form of C-code—due to their structural invariance before the run time of the computation, and before the start of computation the structurally-invariant models can be optimized with the known mathematical methods for minimizing computation effort, therefore for example, by BLT transforms, tearing or sparse-matrix methods. From the run time-optimized algorithmic model then a process model which can be executed on the process computer can be prepared, therefore, for example, by completion of the above cited C-code.
More complex process models are, however, often structurally variant, they have different modes which are characterized in that, for example, different combinations of state variables or different relationships between a choice of state variables which remains the same describe the functionality of the process model, these different modes of the process model being activated or deactivated depending on certain conditions. A structurally variant differential-algebraic model is called a hybrid DAP. When the conditions are bivalent, a hybrid DAP with n conditions has a total of 2n possible modes. Depending on the state variables of the process model, therefore different parts of the hybrid DAP are activated or deactivated so that a special mode of the hybrid DAP is less complex (in the sense of comprehensive) than the hybrid DAP which is omnipotent and encompasses all possible modes.
Hybrid DAPs are transferred into an executable, mode-aspecific process model which then altogether underlies the computation process with all the conditions which occur in them, which are linked to the state variables, and which lead to different modes of the hybrid DAP. The complexity of this hybrid DAP alone entails major difficulties due to the in part considerable size of these process models, especially difficulties with respect to real time computation capacity. In addition, hybrid DAPs cannot be well optimized mathematically due to the case differences contained in them; this is likewise disadvantageous for the run time behavior.
In order to be able to carry out the computation process, in each time step based on a more slender, mode-specific process model, it is conceivable to extract from the hybrid DAP all possible mode-specific DAPs, each of these mode-specific DAPs being stripped of case differences and thus all parts of the hybrid DAP which are not needed, as a result of which each mode-specific DAP can be optimized with known mathematical methods and can be transferred into a “fast”, executable mode-specific process model. The totality of all possible executable mode-specific process models can then be supplied to a group of executable mode-specific process models. This procedure is problematic in practice since the group of executable mode-specific process models can be extremely large (2n executable mode-specific process models for n binary case differences) and entails a considerable memory demand and moreover the preprocessing of the hybrid DAP can be very tedious. Often, this also applies when prior to real time execution the modes which actually occur are known and not all possible executable mode-specific process models, but only certain executable mode-specific process models, need be generated and extracted.
In one computation process, by evaluating the state variables a current mode of the hybrid DAP is then determined, in deviation of the current mode of the hybrid DAP from the mode of the hybrid DAP which applies beforehand, an executable mode-specific process model which corresponds to the current mode is selected from the group of executable mode-specific process models and further computation is based on it.